Tarefa paper_repro.cheng_hoekstra_2013.tab5_pb_c1.tool
paper_reprotoolT1publicépoca 1, tentativa 1Execução: 20261015T183517Z-suite-paper_repro-gemini-0cda63Veredito
Pergunta feita ao analista
Tarefa de ferramenta: nenhuma pergunta; a especificação de referência é chamada direto.
Valores esperados e de onde vêm
cheng_hoekstra_2013.tab5_pb_c1.software
- Fonte
- statsmodels 0.15.0: the reference specification of cheng_hoekstra_2013 tab5_pb_c1 (infer.ols, figure 'coef.cdl') on an independent code path
- Tipo
- software
- Localização
- cheng_hoekstra_2013: NBER Working Paper 18134, Table 5, Panel B 'Log Homicide Rate (OLS - Unweighted)', column (1) state and year fixed effects, row 'Castle Doctrine Law'
- Valor
- 0,0877014
0.08770138490539588(se 0,06689910.06689912458805553) - Conferido por
- execução de software · sm.OLS(l_homicide, add_constant(['cdl']), fe dummies ['sid', 'year']; 61 independent columns).fit(cov_type='cluster', groups=sid) on castle (the file pinned at sha256 804633c161827b6c0824f86f239046386d1a8266a866f83bf5ddb2aa762a5f29); n_obs = 550. The tool infer.ols (magi_infer, numpy) does not call statsmodels. Written by scripts/paper_repro_reference.py.
- Implementação
- independente da ferramenta
- Endereço
https://pypi.org/project/statsmodels/0.15.0/
- #0 figura próxima: 0,0877014
0.08770138490539588· relativa 0.000001 · absoluta 6.689912458805552e-8 - #1 figura próxima: 0,0668991
0.06689912458805553· relativa 0.000001 · absoluta 6.689912458805552e-8
cheng_hoekstra_2013.tab5_pb_c1.paper
- Fonte
- Cheng, C. and Hoekstra, M. (2013). Does Strengthening Self-Defense Law Deter Crime or Escalate Violence? Evidence from Expansions to Castle Doctrine. Journal of Human Resources 48(3): 821-854. Cells read from the NBER Working Paper 18134 (June 2012).
- Tipo
- paper
- Localização
- NBER Working Paper 18134, Table 5 (the effect of castle doctrine on homicide), Panel B 'Log Homicide Rate (OLS - Unweighted)', column (1), row 'Castle Doctrine Law'
- Página
- 38
- Trecho
Panel B: Castle Doctrine Law 0.0877 (0.0638)
- Valor como publicado
0.0877- Erro-padrão como publicado
0.0638- Valor
- 0,0877
0.0877(se 0,06380.0638) log points of the homicide rate per unit of the castle doctrine law variable - Conferido por
- fonte primária · Read on 2026-10-15 from the NBER Working Paper 18134 PDF (43 pages, created 2012-06-28) with pdftotext -layout and from the page image rendered at 80 dpi: Table 5 'The Effect of Castle Doctrine on Homicide' is on PDF page 40 (printed page 38). The published JHR version (48(3), 2013) could not be read without a subscription, so the cells are the authors' circulated working-paper version. The notes say 'Robust standard errors are clustered at the state level'; the unit is the state-year; 550 observations in every column. Panel A is weighted (by state population, 'OLS - Weighted'), Panel B unweighted. Column (1) has state and year fixed effects; column (2) adds region-by-year fixed effects.
- sha256 da cópia lida
1283a9c1e37ea2114e36b6c48ffc7c3fc0f26b2334f08c1a60ffbe82f3005682(identifica a cópia lida, não um arquivo canônico)- Desvio conhecido
- convenção de erro-padrãoFound in the software-reference run (scripts/paper_repro_reference.py, statsmodels 0.15.0, 2026-10-15), before the MAGI tool ran on this target: the declared specification (state and year effects as dummies, unweighted, CR1 clustered by state counting the dummies in K) gives an SE of 0.0669 against the printed 0.0638, the same ratio of about sqrt((N-k)/(N-K)) (k: the regressors left after absorbing the state effects, as Stata xtreg, fe counts them; K: the full dummy count) as Panel A, while the coefficient matches the printed one: the authors' clustered errors do not count the state effects, nested in the clusters, in K (Stata xtreg, fe). The reference keeps the declared convention; the printed cell is recorded and non-required on T1.
- Endereço
https://www.nber.org/system/files/working_papers/w18134/w18134.pdf- Licença
- NBER working paper, copyright the authors; cited, not reproduced.
- #2 figura próxima: 0,0877
0.0877· published_cell d=4 · absoluta 0.000050001000000000005 - #3 figura próxima: 0,0638
0.0638· published_cell d=4 (the SE as printed) · absoluta 0.000050001000000000005
Verificações
| # | Verificação | Obrigatória | Resultado | Esperado | Observado | Tolerância | Fonte | Chamada |
|---|---|---|---|---|---|---|---|---|
| 0 | figura próxima 0.08770138491 vs 0.08770138490539588 | obrigatória | passou | 0,08770140.08770138490539588 | 0,08770140.08770138490539615 | relativa 0.000001 · absoluta 6.689912458805552e-8 | cheng_hoekstra_2013.tab5_pb_c1.software | — |
| 1 | figura próxima 0.06689912459 vs 0.06689912458805553 | obrigatória | passou | 0,06689910.06689912458805553 | 0,06689910.06689912458805584 | relativa 0.000001 · absoluta 6.689912458805552e-8 | cheng_hoekstra_2013.tab5_pb_c1.software | — |
| 2 | figura próxima 0.08770138491 vs 0.0877 | obrigatória | passou | 0,08770.0877 | 0,08770140.08770138490539615 | published_cell d=4 · absoluta 0.000050001000000000005 | cheng_hoekstra_2013.tab5_pb_c1.paper | — |
| 3 | figura próxima 0.06689912459 vs 0.0638 | registrada | falhou | 0,06380.0638 | 0,06689910.06689912458805584 | published_cell d=4 (the SE as printed) · absoluta 0.000050001000000000005 | cheng_hoekstra_2013.tab5_pb_c1.paper | — |
Caminho de referência e caminho do agente
A chamada de referência ao lado da chamada que deu a resposta, argumento por argumento.
a própria especificação da tarefa
| Argumento | Referência | Agente | |
|---|---|---|---|
| cluster | "sid" | "sid" | igual |
| controls | [] | [] | igual |
| dataset | "castle" | "castle" | igual |
| fe | ["sid","year"] | ["sid","year"] | igual |
| intercept | — | true | não fixado pela referência |
| level | — | 0,950.95 | não fixado pela referência |
| se | — | "HC1" | não fixado pela referência |
| subset | — | — | não fixado pela referência |
| weights | — | — | igual |
| x | ["cdl"] | ["cdl"] | igual |
| y | "l_homicide" | "l_homicide" | igual |
Trajetória
Cada evento na ordem em que aconteceu: turnos do modelo, chamadas de ferramentas, guardas, transformações e pontuação.
- 0Início
Tarefa de ferramenta: nenhuma pergunta; a especificação de referência é chamada direto.
castle(agent)The state-year panel of Cheng and Hoekstra (2013), 'Does Strengthening Self-Defense Law Deter Crime or Escalate Violence? Evidence from Expansions to Castle Doctrine', as distributed with Cunningham's Causal Inference: The Mixtape: one row per U.S. state and year, 2000-2010 (550 rows: 50 states, 11 years). Columns used most: state, the state's name; sid, a numeric state id; year; cdl, the castle doctrine law variable as the paper codes it: the fraction of the year in which the state's castle doctrine (stand-your-ground) law was in effect, 0 before adoption and 1 in full years after it; post, 1 in every year from the adoption year on (any part of the year); effyear and treatment_date, the year the law took effect (missing for states that never adopted one); homicide, the homicide rate per 100,000 residents (FBI Uniform Crime Reports), and l_homicide its natural log; murder and l_murder, the murder rate and its log; population; popwt, the state's average population over 2000-2010 (constant within a state), the weight the paper's weighted regressions use; northeast, midwest, south, west, census region indicators; r20001 to r20104, region-by-year indicators named r20<two-digit year><region 1-4> (for example r20063 is region 3 in 2006); trend_1 to trend_51, state-specific linear trends; lead1 to lead9 and lag0 to lag5, event-time indicators relative to adoption; other crime rates (robbery, assault, burglary, larceny, motor) and their logs (l_robbery and so on); and the time-varying controls of the paper (police, unemployrt, income, poverty, prisoner, lagprisoner, exp_subsidy, exp_pubwelfare, and the shares of black and white men aged 15-24 and 25-44).
file804633c161827b6c0824f86f239046386d1a8266a866f83bf5ddb2aa762a5f29· frame — - 1Ferramenta
infer.olsv0.1.0call_fc7364cfdecidido pelo códigoreexecutávelArgumentos
{ "cluster": "sid", "controls": [], "dataset": "castle", "fe": [ "sid", "year" ], "intercept": true, "level": 0.95, "se": "HC1", "subset": null, "weights": null, "x": [ "cdl" ], "y": "l_homicide" }Figuras call_fc7364cf Chave Valor Valor bruto Erro-padrão IC coef.cdl Coefficient on cdl in the regression of l_homicide0,0877014 0.087701384905396150,0668991 0.06689912458805584-0,0467374 – 0,22214 Diagnósticosn_obs= 550550k= 6161r2= 0,9105470.9105468478338682df_resid= 489489se_type="cluster"n_clusters= 5050fixed_effects="sid (50 levels), year (11 levels)"
Tabelas (1)
{ "coefficients": [ { "ci_high": 2.035267779456797, "ci_low": 1.8549305947048351, "coef": 1.945099187080816, "p": 9.62431952152882e-41, "se": 0.04486947824097916, "t": 43.350162813000196, "term": "Intercept" }, { "ci_high": 0.222140209063177, "ci_low": -0.0467374392523847, "coef": 0.08770138490539615, "p": 0.1959855599903869, "se": 0.06689912458805584, "t": 1.3109496640716034, "term": "cdl" } ] }- Digests dos dados
castle6a9af2b4a14b985d82e0f3aea93c535c24cfc2497c4d9f07242bac5f84ae11c1- sha256 do resultado
9e31b5d4029a9aebe7c582f97547c28ae7928a71fa60025542b9db358a9bf0dc
- 2Pontuação#0figura próximapassouobrigatória
0.08770138491 vs 0.08770138490539588 - 3Pontuação#1figura próximapassouobrigatória
0.06689912459 vs 0.06689912458805553 - 4Pontuação#2figura próximapassouobrigatória
0.08770138491 vs 0.0877 - 5Pontuação#3figura próximafalhouregistrada
0.06689912459 vs 0.0638
Épocas × verificações
| # | 0 | 1 | 2 | 3 |
|---|---|---|---|---|
| Época 1 | passou | passou | passou | falhou |
Tentativas
Cada tentativa é seu próprio arquivo e é publicada; só a última de cada época é pontuada.
- época 1, tentativa 1passoupontuada(exibindo)
Downloads desta tarefa
376ad501113a8b4edf57a4d6830d64249ebf5661a8169b3b43b67e9ddc937300O hash de um zip é só de transporte: o que ancora a integridade é o RUN_SHA256SUMS que vai dentro dele, cópia exata do SHA256SUMS da execução.
| Arquivo | Tamanho | sha256 |
|---|---|---|
| sources/cheng_hoekstra_2013.tab5_pb_c1.paper.json | 2,7 KB | f83d51e7deab5dfe1145eba61b515167ae263650219df09f7a0573362aeebd80 |
| sources/cheng_hoekstra_2013.tab5_pb_c1.software.json | 1,3 KB | afc756ac6934e7684ba49d2ec19498261def6fd386c6a898c72589aa07ebfd82 |
| specs/paper_repro.cheng_hoekstra_2013.tab5_pb_c1.tool.json | 6,5 KB | 554433dc42fa27ce7c6e9b6880b3e1f2a96b9190bd744bffcda222be3d23bcff |
| traces/paper_repro.cheng_hoekstra_2013.tab5_pb_c1.tool.e1.a1.jsonl | 3,5 KB | 9cde88767742997c6d4b7ded50b86dc59a86c4cfb42264b1bf886d5c9ba36c60 |
| trajectories/paper_repro.cheng_hoekstra_2013.tab5_pb_c1.tool.e1.a1.jsonl | 8,3 KB | 00378dffb3c6af9119712db37c122263ea85a997ffaf9a000eb7d89a79d2bb5c |